Kosovo_Covid 19_AS2018572

library(devtools)
devtools::install_github("thiyangt/sta3262")
library(sta3262)
get_individual_project_country("AS2018572")

[1] "Kosovo"

Kosovo

##loading packages
library(tidyverse)
library(magrittr)
library(coronavirus)
library(tidyr)
library(norm)
coronavirus$cases <- abs(coronavirus$cases)
coronavirus <- as.data.frame(coronavirus, stringAsFactors = TRUE)
Kosovo_corona <- coronavirus %>% filter(country == "Kosovo")


library(ggplot2)
library(maptools)
library(tibble)
library(ggrepel)
library(png)
library(grid)
library(sp)
library(ggmap)
library(plotly)
library(dplyr)
library(RColorBrewer)
library(gapminder)
library(gifski)

Introduction of the country

The National Flag of Kosovo

Location of Kosovo in World map

data(wrld_simpl)
p <- ggplot() +
  geom_polygon(
    data =wrld_simpl,
    aes(x = long, y = lat, group = group), fill = "gray", colour = "white"
  ) +
  coord_cartesian(xlim = c(-180, 180), ylim = c(-90, 90)) +
  scale_x_continuous(breaks = seq(-180, 180, 120)) +
  scale_y_continuous(breaks = seq(-90, 90, 100))

p +
  geom_point(
    data = Kosovo_corona , aes(x = long, y = lat), color = "red", size
    = 1
  )

fr <- c(left = 14, bottom = 38, right = 27, top = 48)
fond <- get_stamenmap(fr, zoom = 5,"toner-lite")
Kosovo <- data.frame(lon=20.9,lat=42.6)
ggmap(fond)+geom_point(data=Kosovo,aes(x=lon,y=lat),color="red",size=2)

Kosovo is the European country as shown above.Kosovo, self-declared independent country in the Balkans region of Europe.

Climate condition of Kosovo

The climate of Kosovo is predominantly continental, resulting in warm summers and cold winters with Mediterranean and Alpine influences (average temperature within the country range from +30 °C (summer) to –10 °C (winter)). However, due to unequal elevations in certain parts of the country, there are differences in temperature and rainfall distribution. December and January are regarded as the coldest months, July and August as the warmest months of the year. The maximum rainfall rate is reached between October and December. Between November and March, snowfall can be expected in Kosovo, even in the flat parts of the country. The highest snowfall rates can be expected in the mountain regions of Kosovo. The valley between Mitrovica and Kaçanik belongs to the dryer areas of the country. In contrast, the plain of Dukagjini between Peja and Prizren is described as a very fertile area with more precipitation between November and March. Based on the climate conditions, Kosovo can be separated into three climatic areas:

• Climatic Area of Kosovo (Kosovo Plain),
• Climatic Area of Dukagjini (Dukagjini Plain) and
• Climatic Area of mountains and forest parts.

The climatic area of Kosovo (Kosovo Plain), which includes the Iber valley, is influenced by continental air masses. For this reason, in this part of the country, the winters are colder with medium temperatures above –10 °C, but sometimes down to –26 °C. The summers are very hot with average temperatures of 20 °C, sometimes up to 37 °C. This area is characterized by a dry climate and a total annual precipitation of 600 mm per year, approximately. The climatic area of Dukagjini (Dukagjini Plain), which includes the watershed of the Drini i Bardh river, is influenced very much by the hot air masses, which cross the Adriatic Sea. Medium temperatures during winter range from 0.5 °C to sometimes 22.8 °C. The average annual precipitation of this climatic area is about 700 mm per year. The winter is characterized by heavy snowfalls.

Kosovo whether,climate and geography

Lock-down status of the Kosovo

Since the first COVID-19 case was registered in Kosovo on 13 March 2020.The Kosovar government on july 28 2020 imposed most of the previous lockdown measures, such as banning religious ceremonies and other activities, in an effort to prevent an alarming escalation of coronavirus cases.In these day the government ordered that public gatherings, including family traditional ceremonies and mass gathering of more than five people, were banned in squares or parks. Restaurants, cafes, night clubs cannot operate during 10.30 p.m. until 5 a.m.Citizens from neighboring Western Balkan countries where new virus cases had risen too need to present a negative virus test to enter the country.Citizens were advised to wear the mask in all closed buildings or spaces and institutions and companies should create the proper social distancing environment for the employees. While the number of new COVID-19 cases in Kosovo rose sharply in November 2020, with a weekly average of 715 new cases, the number started to significantly decline from mid-December. In January, Kosovo recorded a weekly average of 300 new cases, bringing the total number of reported cases to more than 58 000 since the beginning of the epidemic.Regarding measures put in place to help contain the spread of the virus, restrictions on freedom of movement remain in place across the country for people over the age of 65, who are only permitted to leave the house between 06:00-10:00 and 16:00-19:00. Weddings and religious ceremonies continue to be prohibited, while funerals may only be conducted with immediate family members.Since 23 December 2020 , controls at the borders also remain in force with both Kosovo citizens and most foreign nationals still required to present a negative PCR test when entering Kosovo, or undergo a seven-day self-isolation period following arrival. On 15 January 2021, regulations governing public gatherings have, however, been relaxed throughout Kosovo. The number of people permitted to gather in public spaces such as parks, squares and recreational centers has been extended from four to fifty. With Kosovo’s parliamentary election scheduled for 14 February 2021, a special mention is also made for public rallies, which must be limited to 50 persons. Municipalities have continued to be designated as low, medium or high risk depending on the number of infected inhabitants (<75, 76-170, >150 infected individuals per 100 000 inhabitants respectively). Depending on their classification, municipalities face different measures. In low and medium-risk municipalities, operating hours for businesses, shopping centers and cultural institutions have now been extended by two hours to between 05:00 and 22:00. In high-risk municipalities, a curfew remains in force but has been pushed back, now applying from 21:30 until 05:00.

Actions taken by the government

Acting Prime Minister announced that vaccinations against COVID-19 began in last February, with health professionals, people over the age of 65 and at-risk groups being the first to received the vaccine. Estimations are that 20 000 citizens will be vaccinated per day. Agreements were reached with Pfizer/BioNTech, COVAX, and the Austrian state to provide vaccines.

Kosovo’s Health Minister Armend Zemaj says he has been kept in the dark about Serbia’s supposed vaccination campaign

Exploratory Data analysis

Kosovo_corona<- as.data.frame(Kosovo_corona)
head(Kosovo_corona)

        date province country      lat     long      type cases
1 2020-01-22     <NA>  Kosovo 42.60264 20.90298 confirmed     0
2 2020-01-23     <NA>  Kosovo 42.60264 20.90298 confirmed     0
3 2020-01-24     <NA>  Kosovo 42.60264 20.90298 confirmed     0
4 2020-01-25     <NA>  Kosovo 42.60264 20.90298 confirmed     0
5 2020-01-26     <NA>  Kosovo 42.60264 20.90298 confirmed     0
6 2020-01-27     <NA>  Kosovo 42.60264 20.90298 confirmed     0

tail(Kosovo_corona)

           date province country      lat     long      type cases
1813 2021-09-13     <NA>  Kosovo 42.60264 20.90298 recovered    NA
1814 2021-09-14     <NA>  Kosovo 42.60264 20.90298 recovered    NA
1815 2021-09-15     <NA>  Kosovo 42.60264 20.90298 recovered    NA
1816 2021-09-16     <NA>  Kosovo 42.60264 20.90298 recovered    NA
1817 2021-09-17     <NA>  Kosovo 42.60264 20.90298 recovered    NA
1818 2021-09-18     <NA>  Kosovo 42.60264 20.90298 recovered    NA

summary(Kosovo_corona)

      date              province           country               lat      
 Min.   :2020-01-22   Length:1818        Length:1818        Min.   :42.6  
 1st Qu.:2020-06-21   Class :character   Class :character   1st Qu.:42.6  
 Median :2020-11-19   Mode  :character   Mode  :character   Median :42.6  
 Mean   :2020-11-19                                         Mean   :42.6  
 3rd Qu.:2021-04-20                                         3rd Qu.:42.6  
 Max.   :2021-09-18                                         Max.   :42.6  
                                                                          
      long          type               cases       
 Min.   :20.9   Length:1818        Min.   :   0.0  
 1st Qu.:20.9   Class :character   1st Qu.:   0.0  
 Median :20.9   Mode  :character   Median :   7.0  
 Mean   :20.9                      Mean   : 150.9  
 3rd Qu.:20.9                      3rd Qu.: 101.0  
 Max.   :20.9                      Max.   :5241.0  
                                   NA's   :45      

Above table show as Kosovo_corona is consist of the number of confirmed, death and recovered covid-19 patients from 2020-01-22 to 2021-09-18 of the Kosovo and the location of the Kosovo country in the worlds map shown with it’s latitude and longitude.It is located with 20.9 longitute and 42.6 latitude.

Visualization of death, confirmed, recovered, active cases

death cases

death_cases <- filter(Kosovo_corona, type == "death")
death_cases$cases[is.na(death_cases$cases)]<-mean(death_cases$cases,
                                                          na.rm=TRUE)
death_cases$cases<-round(death_cases$cases,digits=0)
ggplot(death_cases,aes(x=date,y= cases))+ geom_path(size=1) + labs(title = "Death cases in Kosovo")

Above graph shows the death number of covid-19 patients in Kosovo in daily basis. It shows that number of death covid-19 patients has been increasing and decreasing.Overall idea of the above graph,Higher death cases in country Kosovo can be see since oct 2020 to june 2021.

confirmed cases

Kosovo confirms first coronavirus cases

confirmed_cases <- filter(Kosovo_corona, type == "confirmed")
confirmed_cases$cases[is.na(confirmed_cases$cases)]<-mean(confirmed_cases$cases,
                                                          na.rm=TRUE)
confirmed_cases$cases<-round(confirmed_cases$cases,digits=0)
ggplot(confirmed_cases,aes(x=date,y= cases,colour = 'red')) + geom_path(size=1) + labs(title = "Confirmed cases in Kosovo")

Above graph shows the confirmed number of covid-19 patients in Kosovo in daily basis. It shows that number of confirmed covid-19 patients has been increasing and decreasing.Overall idea of the above graph,Higher confirmed cases in country Kosovo can be see since after oct 2020.

recovered cases

recovered_cases <- filter(Kosovo_corona, type == "recovered")
recovered_cases$cases[is.na(recovered_cases$cases)]<-mean(recovered_cases$cases,
                                                          na.rm=TRUE)
recovered_cases$cases<-round(recovered_cases$cases,digits=0)
ggplot(recovered_cases, aes(date,cases,colour=20)) + geom_path(size=1) + labs(title = "Recovered cases in Kosovo")

Above graph shows the recoverd number of covid-19 patients in Kosovo in daily basis. It shows that number of recoverd covid-19 patients has been increasing and decreasing.Overall idea of the above graph,Higher recoverd cases in country Kosovo can be see since oct 2020 to jun 2021.

active cases

Kosovo_corona_wider<-Kosovo_corona%>%pivot_wider(names_from = "type",values_from = "cases")
Kosovo_corona_wider<-Kosovo_corona_wider%>%mutate(active=cumsum(confirmed)-cumsum(death)-cumsum(recovered))
Kosovo_corona_wider$active<-replace(Kosovo_corona_wider$active,Kosovo_corona_wider$active<0,0)
ggplot(Kosovo_corona_wider, aes(date, active)) + geom_path(size=1) + labs(title = "Active cases in Kosovo")

Above graph shows the active number of covid-19 patients in Kosovo in daily basis. It shows that the number of active covid-19 patients has been increasing and decreasing.Overall idea of the above graph,the higher active cases in country Kosovo can be see since oct 2020 to jun 2021.

ggplot(Kosovo_corona, aes(date, cases)) + geom_path(size=1) + facet_grid(rows = vars(type)) +
  labs(title = "Confirmed, Death and Recovered cases in Kosovo")

ggplot(Kosovo_corona, aes(x = date, y = cases, colour = type)) + geom_path(size=1) + 
  labs(title="Confirmed, Death and Recovered cases in Kosovo")

Above graph shows the number of confirmed, death and recovered covid-19 patients in Kosovo in daily basis in the same graph. This graph shows that number of patients confirming with covid-19 in a day and number of covid-19 patients recovery in a day has still increased.But number of death cases has still in the lower level over the time period comparing with the number of patients confirming with covid-19 in a day. So,still the this situation has not controlled by the Kosovo and still the its spreading rapidly.

Kosovo_corona<-  Kosovo_corona%>%
  group_by(type)%>%
  mutate(cum_cases = cumsum(cases))

ggplot(Kosovo_corona, aes(date, cum_cases, colour = type)) + geom_path(size = 1) +
  labs(title = "Total number of confirmed, death, recovered cases in Kosovo")

Above graph implies that the total number of covid-19 confirmed cases and covid-19 recovered cases has increased exponentially.Covid-19 recovered cases had parallely increased with Covid-19 confirmed cases over the time.covid-19 death cases has not showing any special characteristic according to above graph over the time.

Kosovo_corona_spread <- spread(select(Kosovo_corona, 1,6,8), key = type, value = cum_cases)

Kosovo_corona_spread$per_confirmed <- (Kosovo_corona_spread$confirmed / Kosovo_corona_spread$confirmed)*100
Kosovo_corona_spread$per_death <- (Kosovo_corona_spread$death / Kosovo_corona_spread$confirmed)*100
Kosovo_corona_spread$per_recovered <- (Kosovo_corona_spread$recovered / Kosovo_corona_spread$confirmed)*100

Kosovo_corona_gather <- gather(Kosovo_corona_spread, key = "type_1" , value = "Per_cum_with_confirmed",5:7)

Kosovo_corona <- cbind.data.frame(Kosovo_corona, select(Kosovo_corona_gather, 5,6))
Kosovo_corona[is.na(Kosovo_corona)] <- 0

ggplot(Kosovo_corona, aes(date, Per_cum_with_confirmed , colour = type)) + geom_path(size=1) +
  labs(title = "Percentage of total death, recovered cases with confirmed cases in Kosovo")

Above graph implies the total number of covid-19 death and covid-19 recovered cases as a percentage with total covid-19 confirmed cases in daily basis. This implies that percentage of total covid-19 recovered patients with the total number of covid-19 confirmed cases is increasing daily and it in a satisfactory level. Also the percentage of total number of covid-19 death cases with total number of covid-19 confirmed cases is slowly increasing after 2021.

Comparison with other countries

coronavirus <- as.data.frame(coronavirus)

data(wrld_simpl)

p <- ggplot() +
  geom_polygon(
    data = wrld_simpl,
    aes(x = long, y = lat, group = group,), fill = "grey", colour = "white"
  ) +
  coord_cartesian(xlim = c(15, 30), ylim = c(35, 50)) +
  scale_x_continuous(breaks = seq(15, 25,30)) +
  scale_y_continuous(breaks = seq(35,45,50))


p +
  geom_point(
    data = coronavirus , aes(x = long, y = lat), color = "red", size
    = 3
  )  + geom_text(aes(x=coronavirus$long, y=coronavirus$lat, label=coronavirus$country))

A landlocked country, Kosovo is bordered by Serbia to the north and east, North Macedonia to the south, Albania to the west, and Montenegro to the northwest. Kosovo, about the same size as Jamaica or Lebanon, is the smallest country in the Balkans.The above map implies the nearby countries to Kosovo.

nearcountries <- subset.data.frame(coronavirus, ( 35< lat & lat < 50) & (15 < long & long < 30) )
count(nearcountries,country)

                  country    n
1                 Albania 1818
2  Bosnia and Herzegovina 1818
3                Bulgaria 1818
4                 Croatia 1818
5                 Czechia 1818
6                  Greece 1818
7                 Hungary 1818
8                  Kosovo 1818
9                 Moldova 1818
10             Montenegro 1818
11        North Macedonia 1818
12                Romania 1818
13                 Serbia 1818
14               Slovakia 1818

The above table shows the list of nearly countries to Kosovo.

nearest_countries <- filter(coronavirus, country == "Albania"|country =="Bosnia and Herzegovina"| country =="Bulgaria"| country =="Croatia"| country =="Czechia"|country =="Greece"|country =="Hungary"|country =="Kosovo"|country ==" Moldova"|country =="Montenegro"|country =="North Macedonia"|country =="Romania"|country =="Serbia"|country =="Slovakia")
count(nearest_countries,country)

                  country    n
1                 Albania 1818
2  Bosnia and Herzegovina 1818
3                Bulgaria 1818
4                 Croatia 1818
5                 Czechia 1818
6                  Greece 1818
7                 Hungary 1818
8                  Kosovo 1818
9              Montenegro 1818
10        North Macedonia 1818
11                Romania 1818
12                 Serbia 1818
13               Slovakia 1818

Above table shows,from the countries near Kosovo,which are in the continent Europe has been sorted to a new data frame for further analysis .

p +
  geom_point(
    data = nearest_countries , aes(x = long, y = lat), color = "red", size
    = 3
  )  + geom_text(aes(x=nearest_countries$long, y=nearest_countries$lat, label=nearest_countries$country))

The above map was generated in order to confirm whether the countries near Kosovo,which are in the Europe continent is in the relevent dataframe. Therefore it can be concluded that the countries near Kosovo,which are in the Europe continent has been considered.

confirmed_nearest_countries <- filter(nearest_countries, type == "confirmed")
death_nearest_countries <- filter(nearest_countries, type == "death")
recovered_nearest_countries <- filter(nearest_countries, type == "recovered")


ggplot(death_nearest_countries, aes(x = date, y = cases, colour = country)) + geom_path(size=0.5) + 
  labs(title="Daily Death cases in the countries in Europe")

Above graph and treemap appear that daily death cases in Kosovo comparatively negligible when compared to other countries in the same continent. Romania,Hungary,Bulgaria,Czechia are the countries which have the high number of daily death cases in the country.

ggplot(confirmed_nearest_countries, aes(x = date, y = cases, colour = country)) + geom_path(size=0.5) + 
  labs(title="Daily Confirmed cases in the countries in Europe")

Above graph and treemap appear that daily confirmed cases in Kosovo comparatively negligible when compared to other countries in the same continent. Romania,Serbia,Hungary,Czechia are the countries which have the high number of daily confirmed cases in the country.

recovered_nearest_countries$cases[is.na(recovered_nearest_countries$cases)]<-mean(recovered_nearest_countries$cases,
                                                          na.rm=TRUE)
recovered_nearest_countries$cases<-round(recovered_nearest_countries$cases,digits=0)
ggplot(recovered_nearest_countries, aes(x = date, y = cases, colour = country)) + geom_path(size=0.5) + 
  labs(title="Daily Recovered cases in the countries in Europe")

`

Above graph and treemap appear that daily recovered cases in Kosovo comparatively negligible when compared to other countries in the same continent. Romania,Czechia,Hungary are the countries which have the high number of daily recovered cases in the country.

ggplot(nearest_countries, aes(date, cases,colour = country)) + geom_path(size=0.5) + facet_grid(rows= vars(type)) +
  labs(title="Daily Confirmed, Death and Recovered cases in Europe")

Kosovo is negligable when compared to other countries.

count(nearest_countries, type)

       type    n
1 confirmed 7878
2     death 7878
3 recovered 7878

nearest_countries <- nearest_countries%>%
  group_by(country,type)%>%
  mutate(cum_cases = cumsum(cases))
nearest_countries

# A tibble: 23,634 x 8
# Groups:   country, type [39]
   date       province country   lat  long type      cases cum_cases
   <date>     <chr>    <chr>   <dbl> <dbl> <chr>     <int>     <int>
 1 2020-01-22 <NA>     Albania  41.2  20.2 confirmed     0         0
 2 2020-01-23 <NA>     Albania  41.2  20.2 confirmed     0         0
 3 2020-01-24 <NA>     Albania  41.2  20.2 confirmed     0         0
 4 2020-01-25 <NA>     Albania  41.2  20.2 confirmed     0         0
 5 2020-01-26 <NA>     Albania  41.2  20.2 confirmed     0         0
 6 2020-01-27 <NA>     Albania  41.2  20.2 confirmed     0         0
 7 2020-01-28 <NA>     Albania  41.2  20.2 confirmed     0         0
 8 2020-01-29 <NA>     Albania  41.2  20.2 confirmed     0         0
 9 2020-01-30 <NA>     Albania  41.2  20.2 confirmed     0         0
10 2020-01-31 <NA>     Albania  41.2  20.2 confirmed     0         0
# ... with 23,624 more rows

Above graph shows the table with total cases relevent to each type and country in daily basis.

ggplot(nearest_countries, aes(date,cum_cases, colour = country)) + geom_path(size=1) +
  facet_grid(rows= vars(type)) + labs(title = "Total no.of confirmed, death, recovered cases in Europe")

Above graph also express that total number of covid-19 confirmed, death and recovered patients in Kosovo in comparatively negligible when compared to the other countries in the same continent.

ggplot(subset(nearest_countries,type == "death"), aes(date,cum_cases, colour = country)) + geom_path(size=1) +
  labs(title = "Total number of death cases in nearest counties")

summary_df <- death_nearest_countries %>% 
  filter(type == "death") %>%
  group_by(country) %>%
  summarise(total_cases = sum(cases)) %>%
  arrange(-total_cases)
summary_df %>% head(20)

# A tibble: 13 x 2
   country                total_cases
   <chr>                        <int>
 1 Romania                      35456
 2 Czechia                      30489
 3 Hungary                      30123
 4 Bulgaria                     19985
 5 Greece                       14433
 6 Slovakia                     12571
 7 Bosnia and Herzegovina       10247
 8 Croatia                       8493
 9 Serbia                        7739
10 North Macedonia               6437
11 Kosovo                        2889
12 Albania                       2574
13 Montenegro                    1839

conf_df <- death_nearest_countries %>% 
  filter(type == "death") %>%
  group_by(country) %>%
  summarise(total_cases = sum(cases)) %>%
  arrange(-total_cases) %>%
  mutate(parents = "death") %>%
  ungroup() 
  
  plot_ly(data = conf_df,
          type= "treemap",
          values = ~total_cases,
          labels= ~ country,
          parents=  ~parents,
          domain = list(column=0),
          name = "death",
          textinfo="label+value+percent parent")

Total number of death cases in Kosovo is higher than the country Montenegro and Albania but less than the countries near Kosovo,which are in the continent Europe.

ggplot(subset(nearest_countries,type == "confirmed"), aes(date,cum_cases, colour = country)) + geom_path(size=1) +
  labs(title = "Total number of confirmed cases in nearest counties")

summary_df <- confirmed_nearest_countries %>% 
  filter(type == "confirmed") %>%
  group_by(country) %>%
  summarise(total_cases = sum(cases)) %>%
  arrange(-total_cases)
summary_df %>% head(20)

# A tibble: 13 x 2
   country                total_cases
   <chr>                        <int>
 1 Czechia                    1690306
 2 Romania                    1144893
 3 Serbia                      860431
 4 Hungary                     817159
 5 Greece                      629498
 6 Bulgaria                    481728
 7 Slovakia                    402066
 8 Croatia                     391109
 9 Bosnia and Herzegovina      225857
10 North Macedonia             186549
11 Albania                     162173
12 Kosovo                      158934
13 Montenegro                  125728

conf_df <- confirmed_nearest_countries %>% 
  filter(type == "confirmed") %>%
  group_by(country) %>%
  summarise(total_cases = sum(cases)) %>%
  arrange(-total_cases) %>%
  mutate(parents = "Confirmed") %>%
  ungroup() 
  
  plot_ly(data = conf_df,
          type= "treemap",
          values = ~total_cases,
          labels= ~ country,
          parents=  ~parents,
          domain = list(column=0),
          name = "Confirmed",
          textinfo="label+value+percent parent")

Above graph shows total number of confirmed cases in Kosovo is less than the countries near Kosovo,which are in the continent Europe but the total number of confirmed cases in Kosovo is higher than the country Montenegr.

ggplot(subset(nearest_countries,type == "recovered"), aes(date,cum_cases, colour = country)) + geom_path(size=1) +
  labs(title = "Total number of recovered cases in nearest counties")

summary_df <- recovered_nearest_countries %>% 
  filter(type == "recovered") %>%
  group_by(country) %>%
  summarise(total_cases = sum(cases)) %>%
  arrange(-total_cases)
summary_df %>% head(20)

# A tibble: 13 x 2
   country                total_cases
   <chr>                        <dbl>
 1 Czechia                    1687507
 2 Romania                    1080562
 3 Hungary                     782263
 4 Bulgaria                    431211
 5 Croatia                     387320
 6 Slovakia                    287812
 7 Bosnia and Herzegovina      222200
 8 North Macedonia             182930
 9 Albania                     162804
10 Kosovo                      138178
11 Montenegro                  131642
12 Greece                      126254
13 Serbia                       63966

conf_df <- recovered_nearest_countries %>% 
  filter(type == "recovered") %>%
  group_by(country) %>%
  summarise(total_cases = sum(cases)) %>%
  arrange(-total_cases) %>%
  mutate(parents = "recovered") %>%
  ungroup() 
  
  plot_ly(data = conf_df,
          type= "treemap",
          values = ~total_cases,
          labels= ~ country,
          parents=  ~parents,
          domain = list(column=0),
          name = "recovered",
          textinfo="label+value+percent parent")

Above graph represent,total number of recovered cases in Kosovo is higher than Serbia,Gress and Monatengro but less than the other countries near Kosovo,which are in the continent Europe.

corona_final <- filter(nearest_countries, date == "2020-11-19")
corona_final_death <- filter(corona_final, type == "death" )
corona_final_death 

# A tibble: 13 x 8
# Groups:   country, type [13]
   date       province country                  lat  long type  cases cum_cases
   <date>     <chr>    <chr>                  <dbl> <dbl> <chr> <int>     <int>
 1 2020-11-19 <NA>     Albania                 41.2  20.2 death    11       657
 2 2020-11-19 <NA>     Bosnia and Herzegovina  43.9  17.7 death    64      2153
 3 2020-11-19 <NA>     Bulgaria                42.7  25.5 death   119      2649
 4 2020-11-19 <NA>     Croatia                 45.1  15.2 death    49      1200
 5 2020-11-19 <NA>     Czechia                 49.8  15.5 death   134      6902
 6 2020-11-19 <NA>     Greece                  39.1  21.8 death    59      1347
 7 2020-11-19 <NA>     Hungary                 47.2  19.5 death    92      3472
 8 2020-11-19 <NA>     Kosovo                  42.6  20.9 death    14       874
 9 2020-11-19 <NA>     Montenegro              42.7  19.4 death     6       420
10 2020-11-19 <NA>     North Macedonia         41.6  21.7 death    26      1423
11 2020-11-19 <NA>     Romania                 45.9  25.0 death   167      9596
12 2020-11-19 <NA>     Serbia                  44.0  21.0 death    29      1116
13 2020-11-19 <NA>     Slovakia                48.7  19.7 death     0       581

p + geom_point(data = corona_final_death, aes(x = long, y = lat, colour = cum_cases), size = 10) +
  geom_text(aes(x=corona_final_death$long, y=corona_final_death$lat, label=corona_final_death$country))+
  labs(title = "Total no.of death cases as at 2020-11-19(mean quantile date)")

Above map exhibit that Kosovo has a low number of covid-19 death cases as at 19-11- 2020 comparing other countries near Kosovo,which are in the Europe continent.According to the above map Romania has a high number of covid-19 death cases at mean quantile date.

corona_final_confirmed <- filter(corona_final, type == "confirmed" )
corona_final_confirmed

# A tibble: 13 x 8
# Groups:   country, type [13]
   date       province country                  lat  long type      cases cum_cases
   <date>     <chr>    <chr>                  <dbl> <dbl> <chr>     <int>     <int>
 1 2020-11-19 <NA>     Albania                 41.2  20.2 confirmed   786     30623
 2 2020-11-19 <NA>     Bosnia and Herzegovina  43.9  17.7 confirmed  1180     76757
 3 2020-11-19 <NA>     Bulgaria                42.7  25.5 confirmed  3899    114435
 4 2020-11-19 <NA>     Croatia                 45.1  15.2 confirmed  3164     93879
 5 2020-11-19 <NA>     Czechia                 49.8  15.5 confirmed  6471    481755
 6 2020-11-19 <NA>     Greece                  39.1  21.8 confirmed  3227     85261
 7 2020-11-19 <NA>     Hungary                 47.2  19.5 confirmed  4512    161461
 8 2020-11-19 <NA>     Kosovo                  42.6  20.9 confirmed   807     32022
 9 2020-11-19 <NA>     Montenegro              42.7  19.4 confirmed   546     29577
10 2020-11-19 <NA>     North Macedonia         41.6  21.7 confirmed  1198     51213
11 2020-11-19 <NA>     Romania                 45.9  25.0 confirmed 10108    393851
12 2020-11-19 <NA>     Serbia                  44.0  21.0 confirmed  6109    104097
13 2020-11-19 <NA>     Slovakia                48.7  19.7 confirmed  1665     91578

p + geom_point(data = corona_final_confirmed, aes(x = long, y = lat, colour = cum_cases), size = 10) +
  geom_text(aes(x=corona_final_confirmed$long, y=corona_final_confirmed$lat, label=corona_final_confirmed$country)) +
  labs(title = "Total number of confirmed cases as at 2020-11-19(mean quantile date)")

Above map shows that Kosovo has a low number of covid-19 confirmed cases as at 19-11-2020 comparing other countries near Kosovo,which are in the Europe continent.According to the above map Czechia has a higher number of covid-19 confirmed cases at mean quantile date.

corona_final_recovered <- filter(corona_final, type == "recovered")
corona_final_recovered

# A tibble: 13 x 8
# Groups:   country, type [13]
   date       province country                  lat  long type      cases cum_cases
   <date>     <chr>    <chr>                  <dbl> <dbl> <chr>     <int>     <int>
 1 2020-11-19 <NA>     Albania                 41.2  20.2 recovered   349     14565
 2 2020-11-19 <NA>     Bosnia and Herzegovina  43.9  17.7 recovered  1145     41031
 3 2020-11-19 <NA>     Bulgaria                42.7  25.5 recovered   847     33327
 4 2020-11-19 <NA>     Croatia                 45.1  15.2 recovered  2192     74865
 5 2020-11-19 <NA>     Czechia                 49.8  15.5 recovered 11806    379380
 6 2020-11-19 <NA>     Greece                  39.1  21.8 recovered     0     23074
 7 2020-11-19 <NA>     Hungary                 47.2  19.5 recovered  1499     36345
 8 2020-11-19 <NA>     Kosovo                  42.6  20.9 recovered   677     19024
 9 2020-11-19 <NA>     Montenegro              42.7  19.4 recovered   334     18744
10 2020-11-19 <NA>     North Macedonia         41.6  21.7 recovered   621     30204
11 2020-11-19 <NA>     Romania                 45.9  25.0 recovered  8203    269590
12 2020-11-19 <NA>     Serbia                  44.0  21.0 recovered     0     31476
13 2020-11-19 <NA>     Slovakia                48.7  19.7 recovered  2771     38717

p + geom_point(data = corona_final_recovered, aes(x = long, y = lat, colour = cum_cases), size = 10) +
  geom_text(aes(x=corona_final_recovered$long, y=corona_final_recovered$lat, label=corona_final_recovered$country)) +
  labs(title = "Total no.of recovered cases as at 2020-11-19(mean quantile date)")

Above map shows that Kosovo has a low number of covid-19 recovered cases as at 19-11-2020 comparing other countries near Kosovo,which are in the Europe continent.According to the above map Czechia has a higher number of covid-19 recovered cases at mean quantile date.

Comparing between new cases and vaccination

Kosovo Vaccine Process

A Kosovo health worker holds his arm after he was vaccinated with the AstraZeneca coronavirus vaccinae shots in the northern Albanian town of Kukes on Saturday, Mar 20, 2021

data("covid19_vaccine")
data("coronavirus")
Kosovo_cases <- coronavirus %>% 
  filter(country == "Kosovo", 
         type == "confirmed") %>%
  arrange(date) %>%
  select(date, cases) %>%
  left_join(
    covid19_vaccine %>% 
      filter(country_region == "Kosovo") %>%
      select(date, people_fully_vaccinated),
    by = "date")

Kosovo_cases$people_fully_vaccinated[is.na(Kosovo_cases$people_fully_vaccinated)]<-mean(Kosovo_cases$people_fully_vaccinated,na.rm=TRUE)
Kosovo_cases$people_fully_vaccinated<-round(Kosovo_cases$people_fully_vaccinated,digits=0)

 head(Kosovo_cases)

        date cases people_fully_vaccinated
1 2020-01-22     0                   87720
2 2020-01-23     0                   87720
3 2020-01-24     0                   87720
4 2020-01-25     0                   87720
5 2020-01-26     0                   87720
6 2020-01-27     0                   87720

tail(Kosovo_cases)

          date cases people_fully_vaccinated
601 2021-09-13   259                  357197
602 2021-09-14   357                  369033
603 2021-09-15   410                  385297
604 2021-09-16   368                  399341
605 2021-09-17   279                  399341
606 2021-09-18   259                   87720

Kosovo_cases <- Kosovo_cases %>%
  mutate(cases_normalized = (cases - min(cases)) / (max(cases) - min(cases)),
         people_fully_vaccinated_normilized = (people_fully_vaccinated - min(people_fully_vaccinated, na.rm = TRUE)) / 
           (max(people_fully_vaccinated, na.rm = TRUE) - 
              min(people_fully_vaccinated, na.rm = TRUE)))

head(Kosovo_cases)

        date cases people_fully_vaccinated cases_normalized
1 2020-01-22     0                   87720                0
2 2020-01-23     0                   87720                0
3 2020-01-24     0                   87720                0
4 2020-01-25     0                   87720                0
5 2020-01-26     0                   87720                0
6 2020-01-27     0                   87720                0
  people_fully_vaccinated_normilized
1                          0.2196619
2                          0.2196619
3                          0.2196619
4                          0.2196619
5                          0.2196619
6                          0.2196619

tail(Kosovo_cases)

          date cases people_fully_vaccinated cases_normalized
601 2021-09-13   259                  357197       0.06084097
602 2021-09-14   357                  369033       0.08386187
603 2021-09-15   410                  385297       0.09631196
604 2021-09-16   368                  399341       0.08644585
605 2021-09-17   279                  399341       0.06553911
606 2021-09-18   259                   87720       0.06084097
    people_fully_vaccinated_normilized
601                          0.8944661
602                          0.9241050
603                          0.9648321
604                          1.0000000
605                          1.0000000
606                          0.2196619

summary(Kosovo_cases)

      date                cases        people_fully_vaccinated
 Min.   :2020-01-22   Min.   :   0.0   Min.   :     0         
 1st Qu.:2020-06-21   1st Qu.:   0.0   1st Qu.: 87720         
 Median :2020-11-19   Median :  47.0   Median : 87720         
 Mean   :2020-11-19   Mean   : 262.3   Mean   : 87720         
 3rd Qu.:2021-04-19   3rd Qu.: 258.8   3rd Qu.: 87720         
 Max.   :2021-09-18   Max.   :4257.0   Max.   :399341         
 cases_normalized  people_fully_vaccinated_normilized
 Min.   :0.00000   Min.   :0.0000                    
 1st Qu.:0.00000   1st Qu.:0.2197                    
 Median :0.01104   Median :0.2197                    
 Mean   :0.06161   Mean   :0.2197                    
 3rd Qu.:0.06078   3rd Qu.:0.2197                    
 Max.   :1.00000   Max.   :1.0000                    

plot_ly(data = Kosovo_cases,
        x = ~ date,
        y = ~ cases_normalized,
        type = "scatter",
        mode = "line",
        name = "Daily Cases (Normalized)") %>%
  add_lines(x = ~ date,
            y = ~ people_fully_vaccinated_normilized,
            name = "Fully Vaccinated - Aggregate (Normalized)") %>%
  layout(title = "Kosovo - Daily New Cases vs. Total Vaccinated Population (Normalized)",
         legend = list(orientation = 'h'),
         yaxis = list(title = "Normalized Daily Cases/Total Vaccinated"),
         xaxis = list(title = ""),
         margin = list(b = 60))

According to above plot,the number of covid-19 daily new cases has been increasing and decreasing over the time same as the vaccination process in Kosovo has been increasing and decreasing over the time period.Accoring to the data ,4257 is the maximum daily new cases which was reported in Kosovo .399341 is the maximum daily vaccinated cases which was reported in Kosovo.

Conclusions and Discussion

The COVID-19 pandemic, also colloquially known simply as coronavirus pandemic, is an ongoing global pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The novel virus was first identified in Wuhan, China, in December 2019; a lockdown in Wuhan and other cities in Hubei province failed to contain the outbreak, and it spread to other parts of mainland China and around the world. The World Health Organization (WHO) declared a Public Health Emergency of International Concern on 30 January 2020, and a pandemic on 11 March 2020.

Kosovo is the European Country.Kosovo was affected by covid -19 same as other countries.Since the first COVID-19 case was registered in Kosovo on 13 March 2020. Above information is consist of the number of confirmed, death and recovered covid-19 patients from 2020-01-22 to 2021-09-18 of the Kosovo.The number of death covid-19 patients,number of confirmed covid-19 patients, number of recovered covid-19 patients have been increasing and decreasing in Kosovo these time period. Overall idea is the higher death cases in country Kosovo can be see since october 2020 to june 2021.Overall idea is the higher confirmed cases in country Kosovo can be see since after october 2020.Overall idea is the Higher recovered cases in country Kosovo can be see since october 2020 to jun 2021.The number of active covid-19 patients has been increasing and decreasing in Kosovo.Overall idea of the above data,the higher active cases in country Kosovo can be see since october 2020 to june 2021.

The number of patients confirming with covid-19 in a day and number of covid-19 patients recovery in a day has still increased.But number of death cases has still in the lower level over the time period comparing with the number of patients confirming with covid-19 in a day. So,still the this situation has not controlled by the Kosovo and still the its spreading rapidly.The total number of covid-19 confirmed cases and covid-19 recovered cases has increased exponentially.Covid-19 recovered cases had parallely increased with Covid-19 confirmed cases over the time.

covid-19 death cases has not showing any special characteristic over the time.The percentage of total covid-19 recovered patients with the total number of covid-19 confirmed cases is increasing daily and it in a satisfactory level. Also the percentage of total number of covid-19 death cases with total number of covid-19 confirmed cases is slowly increasing after 2021.

The daily confirmed cases in Kosovo comparatively negligible when compared with other nearby countries in the same continent. Romania,Serbia,Hungary,Czechia are the countries which have the high number of daily confirmed cases in the country.Romania,Hungary, Bulgaria,Czechia are the countries which have the high number of daily death cases in the country and daily recovered cases in Kosovo comparatively negligible when compared to other countries in the same continent.Romania,Czechia,Hungary are the countries which have the high number of daily recovered cases in the country.

Total number of confirmed cases in Kosovo is less than the countries near Kosovo,which are in the continent Europe but the total number of confirmed cases in Kosovo is higher than the country Montenegr.Total number of death cases in Kosovo is higher than the country Montenegro and Albania but less than the countries near Kosovo,which are in the continent Europe and total number of death cases in Kosovo is higher than Serbia,Gress and Monatengro but less than the other countries near Kosovo,which are in the continent Europe.

Kosovo has a low number of covid-19 confirmed cases,death cases and recovered cases as at 19-11-2020 which is the mean quantile comparing other countries near Kosovo. Romania has a high number of covid-19 death cases at mean quantile date.Czechia has a higher number of covid-19 confirmed and recovered cases at mean quantile date.

In Kosovo,the number of covid-19 daily new cases has been increasing and decreasing over the time.According to the plot(“Kosovo - Daily New Cases vs. Total Vaccinated Population (Normalized)”),highest number of covid-19 daily cases have confirmed in 29th march 2021.The vaccination process in Kosovo has been increasing and decreasing over the time period.According to the data ,4257 is the maximum daily new cases which was reported in Kosovo .399341 is the maximum daily vaccinated cases which was reported in Kosovo.

Covid-19: Kosovo during pandemic COVID-19

References

• https://kosovo-mining.org/kosovo/climatic-conditions/?lang=en

• https://www.rdocumentation.org/packages/maptools/versions/1.1-2/topics/wrld_simpl

• https://stackoverflow.com/questions/22038640/labeling-center-of-map-polygons-in-r-ggplot

• https://www.britannica.com/place/Kosovo

• https://apnews.com/article/virus-outbreak-religion-travel-international-news-sports-9456102fcf942d9e476c9000a1591a59

• https://www.oecd.org/south-east-europe/COVID-19-Crisis-in-Kosovo.pdf

• https://community.rstudio.com/t/rmarkdown-color-text/34382

• https://www.r-bloggers.com/2021/05/partial-dependence-plots-with-tidymodels-and-dalex-for-tidytuesday-mario-kart-world-records/

• https://lrouviere.github.io/VISU/pres_dataviz.pdf

• https://stackoverflow.com/questions/8161836/how-do-i-replace-na-values-with-zeros-in-an-r-dataframe

• https://github.com/RamiKrispin/coronavirus/blob/master/vignettes/covid19_vaccine.Rmd